scholarly journals Quantile-specific heritability of sibling leptin concentrations and its implications for gene-environment interactions

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Paul T. Williams
Keyword(s):  
Environmental Effects ◽  
Framingham Heart Study ◽  
Leptin Receptor ◽  
Genetic Variant ◽  
Third Generation ◽  
Gene Environment ◽  
Heart Study ◽  
Soluble Leptin Receptor ◽  
Regression Slopes ◽  
Age And Sex

Abstract“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., leptin) is high or low relative to its distribution. Leptin concentrations are strongly related to adiposity, whose heritability is quantile dependent. Whether inheritance of leptin concentrations is quantile dependent, and whether this explains the greater heritability in women than men in accordance with their greater adiposity, and explains other gene-environment interactions, remains to be determined. Therefore, leptin and leptin receptor concentrations from 3068 siblings in 1133 sibships from the Framingham Heart Study Third Generation Cohort were analyzed. Free leptin index (FLI) was calculated as the ratio of leptin to soluble leptin receptor concentrations. Full-sib (βFS) regression slopes were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. The analyses showed βFS increased significantly with increasing percentiles of the offspring’s age- and sex-adjusted leptin distribution (Plinear = 0.0001), which was accelerated at the higher concentrations (Pquadratic = 0.0003). βFS at the 90th percentile (0.418 ± 0.066) was 4.7-fold greater than at the 10th percentile (0.089 ± 0.032, Pdifference = 3.6 × 10−6). Consistent with quantile-dependent expressivity, the βFS was greater in female sibs, which was attributable to their higher leptin concentrations. Reported gene-environment interactions involving adiposity and LEP, LEPR, MnSOD, PPARγ, PPARγ2, and IRS-1 polymorphisms were consistent with quantile-dependent expressivity of leptin concentrations. βFS for leptin receptor concentrations and free leptin index also increased significantly with increasing percentiles of their distributions (Plinear = 0.04 and Plinear = 8.5 × 10−6, respectively). In conclusion, inherited genetic and shared environmental effects on leptin concentrations were quantile dependent, which likely explains male–female differences in heritability and some gene-environment interactions.

scholarly journals Quantile-dependent expressivity of plasma adiponectin concentrations may explain its sex-specific heritability, gene-environment interactions, and genotype-specific response to postprandial lipemia

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10099 ◽  
Author(s):  
Paul T. Williams
Keyword(s):  
Alcohol Consumption ◽  
Genetic Variant ◽  
Postprandial Lipemia ◽  
Specific Response ◽  
Plasma Adiponectin ◽  
Gene Environment ◽  
Heart Study ◽  
Postprandial Response ◽  
Regression Slopes ◽  
Age And Sex

Background “Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. adiponectin) is high or low relative to its distribution. We have previously shown that the heritability (h2) of adiposity, lipoproteins, postprandial lipemia, pulmonary function, and coffee and alcohol consumption are quantile-specific. Whether adiponectin heritability is quantile specific remains to be determined. Methods Plasma adiponectin concentrations from 4,182 offspring-parent pairs and 1,662 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (βOP,h2 = 2βOP/(1 + rspouse)) and full-sib regression slopes (βFS, h2 = {(1 + 8rspouseβFS)0.05-1}/(2rspouse)) were robustly estimated by quantile regression with nonparametric significance assigned from 1,000 bootstrap samples. Results Quantile-specific h2 (± SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted adiponectin distribution when estimated from βOP (Ptrend = 2.2 × 10−6): 0.30 ± 0.03 at the 10th, 0.33 ± 0.04 at the 25th, 0.43 ± 0.04 at the 50th, 0.55 ± 0.05 at the 75th, and 0.57 ± 0.08 at the 90th percentile, and when estimated from βFS (Ptrend = 7.6 × 10−7): 0.42 ± 0.03 at the 10th, 0.44 ± 0.04 at the 25th, 0.56 ± 0.05 at the 50th, 0.73 ± 0.08 at the 75th, and 0.79 ± 0.11 at the 90th percentile. Consistent with quantile-dependent expressivity, adiponectin’s: (1) heritability was greater in women in accordance with their higher adiponection concentrations; (2) relationships to ADIPOQ polymorphisms were modified by adiposity in accordance with its adiponectin-lowering effect; (3) response to rosiglitazone was predicted by the 45T> G ADIPOQ polymorphism; (4) difference by ADIPOQ haplotypes increased linearly with increasing postprandial adiponectin concentrations. Conclusion Adiponectin heritability is quantile dependent, which may explain sex-specific heritability, gene-environment and gene-drug interactions, and postprandial response by haplotypes.

scholarly journals Quantile-Dependent Expressivity of Serum Uric Acid Concentrations

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Paul T. Williams
Keyword(s):  
Uric Acid ◽  
Serum Uric Acid ◽  
Effect Size ◽  
Genetic Variant ◽  
Genetic Effect ◽  
Obese Patients ◽  
Processed Meats ◽  
Gene Environment ◽  
Heart Study ◽  
Regression Slopes

Objective. “Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., serum uric acid) is high or low relative to its distribution. Analyses were performed to test whether serum uric acid heritability is quantile-specific and whether this could explain some reported gene-environment interactions. Methods. Serum uric acid concentrations were analyzed from 2151 sibships and 12,068 offspring-parent pairs from the Framingham Heart Study. Quantile-specific heritability from offspring-parent regression slopes ( β OP , h 2 = 2 β OP / 1 + r spouse ) and full-sib regression slopes ( β FS , h 2 = 1 + 8 r spouse β FS 0.5 − 1 / 2 r spouse ) was robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. Results. Quantile-specific h 2 (±SE) increased with increasing percentiles of the offspring’s sex- and age-adjusted uric acid distribution when estimated from β OP   P trend = 0.001 : 0.34 ± 0.03 at the 10th, 0.36 ± 0.03 at the 25th, 0.41 ± 0.03 at the 50th, 0.46 ± 0.04 at the 75th, and 0.49 ± 0.05 at the 90th percentile and when estimated from β FS   P trend = 0.006 . This is consistent with the larger genetic effect size of (1) the SLC2A9 rs11722228 polymorphism in gout patients vs. controls, (2) the ABCG2 rs2231142 polymorphism in men vs. women, (3) the SLC2A9 rs13113918 polymorphism in obese patients prior to bariatric surgery vs. two-year postsurgery following 29 kg weight loss, (4) the ABCG2 rs6855911 polymorphism in obese vs. nonobese women, and (5) the LRP2 rs2544390 polymorphism in heavier drinkers vs. abstainers. Quantile-dependent expressivity may also explain the larger genetic effect size of an SLC2A9/PKD2/ABCG2 haplotype for high vs. low intakes of alcohol, chicken, or processed meats. Conclusions. Heritability of serum uric acid concentrations is quantile-specific.

scholarly journals Comparison of two methods for analysis of gene–environment interactions in longitudinal family data: the Framingham heart study

2014 ◽  
Vol 5 ◽  
Author(s):  
Yun Ju Sung ◽  
Jeannette Simino ◽  
Rezart Kume ◽  
Jacob Basson ◽  
Karen Schwander ◽  
...  
Keyword(s):  
Framingham Heart Study ◽  
Family Data ◽  
Gene Environment ◽  
Heart Study

scholarly journals Quantile-specific heritability of plasma fibrinogen concentrations

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262395
Author(s):  
Paul T. Williams
Keyword(s):  
Smoking Status ◽  
Genetic Effect ◽  
Disease Status ◽  
Plasma Fibrinogen ◽  
Blood Protein ◽  
Fibrinogen Concentration ◽  
Gene Environment ◽  
Heart Study ◽  
Regression Slopes ◽  
Pollution Exposure

Background Fibrinogen is a moderately heritable blood protein showing different genetic effects by sex, race, smoking status, pollution exposure, and disease status. These interactions may be explained in part by “quantile-dependent expressivity”, where the effect size of a genetic variant depends upon whether the phenotype (e.g. plasma fibrinogen concentration) is high or low relative to its distribution. Purpose Determine whether fibrinogen heritability (h2) is quantile-specific, and whether quantile-specific h2 could account for fibrinogen gene-environment interactions. Methods Plasma fibrinogen concentrations from 5689 offspring-parent pairs and 1932 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (βOP, h2 = 2βOP/(1+rspouse)) and full-sib regression slopes (βFS, h2 = {(1+8rspouseβFS)0.05–1}/(2rspouse)) were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. Results Quantile-specific h2 (±SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted fibrinogen distribution when estimated from βOP (Ptrend = 5.5x10-6): 0.30±0.05 at the 10th, 0.37±0.04 at the 25th, 0.48±0.05 at the 50th, 0.61±0.06 at the 75th, and 0.65±0.08 at the 90th percentile, and when estimated from βFS (Ptrend = 0.008): 0.28±0.04 at the 10th, 0.31±0.04 at the 25th, 0.36±0.03 at the 50th, 0.41±0.05 at the 75th, and 0.50±0.06 at the 90th percentile. The larger genetic effect at higher average fibrinogen concentrations may contribute to fibrinogen’s greater heritability in women than men and in Blacks than Whites, and greater increase from smoking and air pollution for the FGB -455G>A A-allele. It may also explain greater fibrinogen differences between: 1) FGB -455G>A genotypes during acute phase reactions than usual conditions, 2) GTSM1 and IL-6 -572C>G genotypes in smokers than nonsmokers, 3) FGB -148C>T genotypes in untreated than treated diabetics, and LPL PvuII genotypes in macroalbuminuric than normoalbuminuric patients. Conclusion Fibrinogen heritability is quantile specific, which may explain or contribute to its gene-environment interactions. The analyses do not disprove the traditional gene-environment interpretations of these examples, rather quantile-dependent expressivity provides an alternative explanation that warrants consideration.

scholarly journals Quantile-Dependent Heritability of Glucose, Insulin, Proinsulin, Insulin Resistance, and Glycated Hemoglobin

2021 ◽  
pp. 1-25
Author(s):  
Paul T. Williams
Keyword(s):  
Insulin Resistance ◽  
Fasting Glucose ◽  
Tolerance Test ◽  
Alternative Interpretation ◽  
Model Assessment ◽  
Gene Environment ◽  
Heart Study ◽  
Glucose Ratio ◽  
Homeostatic Model Assessment ◽  
Regression Slopes

<b><i>Background:</i></b> “Quantile-dependent expressivity” is a dependence of genetic effects on whether the phenotype (e.g., insulin resistance) is high or low relative to its distribution. <b><i>Methods:</i></b> Quantile-specific offspring-parent regression slopes (β<sub>OP</sub>) were estimated by quantile regression for fasting glucose concentrations in 6,453 offspring-parent pairs from the Framingham Heart Study. <b><i>Results:</i></b> Quantile-specific heritability (<i>h</i><sup>2</sup>), estimated by 2β<sub>OP</sub>/(1 + <i>r</i><sub>spouse</sub>), increased 0.0045 ± 0.0007 (<i>p</i> = 8.8 × 10<sup>−14</sup>) for each 1% increment in the fasting glucose distribution, that is, <i>h</i><sup>2</sup> ± SE were 0.057 ± 0.021, 0.095 ± 0.024, 0.146 ± 0.019, 0.293 ± 0.038, and 0.456 ± 0.061 at the 10th, 25th, 50th, 75th, and 90th percentiles of the fasting glucose distribution, respectively. Significant increases in quantile-specific heritability were also suggested for fasting insulin (<i>p</i> = 1.2 × 10<sup>−6</sup>), homeostatic model assessment of insulin resistance (HOMA-IR, <i>p</i> = 5.3 × 10<sup>−5</sup>), insulin/glucose ratio (<i>p</i> = 3.9 × 10<sup>−5</sup>), proinsulin (<i>p</i> = 1.4 × 10<sup>−6</sup>), proinsulin/insulin ratio (<i>p</i> = 2.7 × 10<sup>−5</sup>), and glucose concentrations during a glucose tolerance test (<i>p</i> = 0.001), and their logarithmically transformed values. <b><i>Discussion/Conclusion:</i></b> These findings suggest alternative interpretations to precision medicine and gene-environment interactions, including alternative interpretation of reported synergisms between <i>ACE, ADRB3</i>, <i>PPAR-γ2</i>, and <i>TNF-α</i> polymorphisms and being born small for gestational age on adult insulin resistance (fetal origin theory), and gene-adiposity (<i>APOE, ENPP1, GCKR, IGF2BP2, IL-6, IRS-1, KIAA0280, LEPR, MFHAS1, RETN, TCF7L2</i>), gene-exercise (<i>INS</i>), gene-diet (<i>ACSL1</i>, <i>ELOVL6</i>, <i>IRS-1</i>, <i>PLIN</i>, <i>S100A9</i>), and gene-socioeconomic interactions.

scholarly journals Association Between Leptin, Cognition, and Structural Brain Measures Among “Early” Middle-Aged Adults: Results from the Framingham Heart Study Third Generation Cohort

2020 ◽  
Vol 77 (3) ◽  
pp. 1279-1289 ◽  
Author(s):  
Victoria Sanborn ◽  
Sarah R. Preis ◽  
Alvin Ang ◽  
Sherral Devine ◽  
Jesse Mez ◽  
...  
Keyword(s):  
Verbal Memory ◽  
Test Performance ◽  
Framingham Heart Study ◽  
Neuropsychological Test ◽  
Normal Weight ◽  
Third Generation ◽  
Effect Modifier ◽  
Heart Study ◽  
Middle Aged Adults ◽  
Plasma Leptin

Background: There is growing interest in the pathophysiological processes of preclinical Alzheimer’s disease (AD), including the potential role of leptin. Human studies have shown that both low and high levels of leptin can be associated with worse neurocognitive outcomes, suggesting this relationship may be moderated by another risk factor. Objective: We examined the association between plasma leptin levels and both neuropsychological test performance and structural neuroimaging and assessed whether body mass index (BMI) is an effect modifier of these associations. Methods: Our study sample consisted of 2,223 adults from the Framingham Heart Study Third Generation Cohort (average age = 40 years, 53% women). Results: Among the entire sample, there was no association between leptin and any of the neuropsychological domain measures or any of the MRI brain volume measures, after adjustment for BMI, APOE4, and other clinical factors. However, we did observe that BMI category was an effect modifier for the association between leptin and verbal memory (p for interaction = 0.03), where higher levels of leptin were associated with better performance among normal weight participants (BMI 18.5–24.9) kg/m2 (beta = 0.12, p = 0.02). No association was observed between leptin level and verbal memory test performance among participants who were overweight or obese. Conclusion: These findings suggest that the association between leptin and cognitive function is moderated by BMI category. Prospective examination of individuals transitioning from middle age to older adulthood will help to clarify the contribution of leptin to AD and other neurodegenerative conditions.

scholarly journals Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9145 ◽  
Author(s):  
Paul T. Williams
Keyword(s):  
Quantile Regression ◽  
Population Distribution ◽  
Genetic Effect ◽  
Forced Expiratory Volume ◽  
Gene Environment ◽  
Heart Study ◽  
Significance Levels ◽  
Forced Expiratory Flow ◽  
Expiratory Flow ◽  
Regression Slopes

Background “Quantile-dependent expressivity” refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and the FEV1/FVC ratio are moderately heritable spirometric traits. The aim of the analyses is to test whether their heritability (h2) is constant over all quantiles of their distribution. Methods Quantile regression was applied to the mean age, sex, height and smoking-adjusted spirometric data over multiple visits in 9,993 offspring-parent pairs and 1,930 sibships from the Framingham Heart Study to obtain robust estimates of offspring-parent (βOP), offspring-midparent (βOM), and full-sib regression slopes (βFS). Nonparametric significance levels were obtained from 1,000 bootstrap samples. βOPs were used as simple indicators of quantile-specific heritability (i.e., h2 = 2βOP/(1+rspouse), where rspouse was the correlation between spouses). Results βOP ± standard error (SE) decreased by 0.0009 ± 0.0003 (P = 0.003) with every one-percent increment in the population distribution of FEV1/FVC, i.e., βOP ± SE were: 0.182 ± 0.031, 0.152 ± 0.015; 0.136 ± 0.011; 0.121 ± 0.013; and 0.099 ± 0.013 at the 10th, 25th, 50th, 75th, and 90th percentiles of the FEV1/FVC distribution, respectively. These correspond to h2 ± SEs of 0.350 ± 0.060 at the 10th, 0.292 ± 0.029 at the 25th, 0.262 ± 0.020 at the 50th, 0.234 ± 0.025 at the 75th, and 0.191 ± 0.025 at the 90th percentiles of the FEV1/FVC ratio. Maximum mid-expiratory flow (MMEF) h2 ± SEs increased 0.0025 ± 0.0007 (P = 0.0004) with every one-percent increment in its distribution, i.e.: 0.467 ± 0.046, 0.467 ± 0.033, 0.554 ± 0.038, 0.615 ± 0.042, and 0.675 ± 0.060 at the 10th, 25th, 50th, 75th, and 90th percentiles of its distribution. This was due to forced expiratory flow at 75% of FVC (FEF75%), whose quantile-specific h2 increased an average of 0.0042 ± 0.0008 for every one-percent increment in its distribution. It is speculated that previously reported gene-environment interactions may be partially attributable to quantile-specific h2, i.e., greater heritability in individuals with lower FEV1/FVC due to smoking or airborne particles exposure vs. nonsmoking, unexposed individuals. Conclusion Heritabilities of FEV1/FVC, MMEF, and FEF75% from quantile-regression of offspring-parent and sibling spirometric data suggest their quantile-dependent expressivity.

Sign in / Sign up

Export Citation Format

Share Document